Candidate: Dr. Erick Forno is a pediatric pulmonologist with a strong background in asthma research. He graduated medical school from Cayetano Heredia University (Per), did residency in Pediatrics at Children's Hospital of Denver (2006) and fellowship at Children's Hospital Boston / Harvard Medical School (2009). He also has a Master's in Public Health (MPH) from Harvard School of Public Health (2009). His main scientific interest is the association between childhood obesity and asthma. He is author or co-author of 31 manuscripts, 26 of which are on the epidemiology and genetic epidemiology of childhood asthma. In 2013 he was elected to the Society of Pediatric Research (SPR). Environment: Children's Hospital of Pittsburgh (CHP) of UPMC, affiliated with the University of Pittsburgh School of Medicine, is a leading pediatric center for clinical care, research, and education excellence. Dr. Forno works in the new Rangos Research Center, comprised of 10 floors of state-of-the-art laboratories, offices, and conference facilities. With a variety of scietific conferences and meetings held at CHP, the School of Medicine, and the Graduate School of Public Health, as well as world-class research faculty, the University of Pittsburgh offers exceptional opportunities to young investigators. In addition to superb mentoring by Dr. Juan Celedn, Dr. Forno's primary mentor, institutional commitment includes >80% research protected time; dedicated office space and resource allocation; shared personnel including a genetic statistician, database manager, and laboratory staff; and guaranteed salary support until July 2016. The University of Pittsburgh Genomics and Proteomics Core Laboratories (GPCL) offers full laboratory and bioinformatics support for genome-wide (GW) genotyping, DNA methylation, and gene expression analysis, on both Illumina and Affymetrix platforms. Research: SIGNIFICANCE: Childhood asthma and obesity are major public health problems. While there is ample evidence of a relationship between both and increased recognition of an obese asthmatic phenotype, the underlying mechanisms are still unclear. In this project we aim to better characterize sub-phenotypes of obese asthma in children, and to identify underlying genetic, epigenetic, and genomic mechanisms. This will allow us to better recognize specific groups of patients and identify novel biomarkers and treatment approaches. INNOVATION: The proposed research represents a significant departure from the status quo, which defines obese asthma solely based on high body mass index (BMI) and assumes all obese asthmatic children are similar. It is also innovative because it will integrate enhanced phenotyping with genome-wide (GW) epigenetic and genomic data in order to identify biologically plausible genetic variants. AIMS: Our hypothesis is that obese asthma is heterogeneous and comprised of several sub-phenotypes, each with specific genetic and genomic pathways. Our specific aims are: 1) To define obese asthmatic subphenotypes via unsupervised analysis and validate them in external cohorts; 2) To identify epigenetic and genomic pathways associated with such enhanced phenotypes, using GW DNA methylation and expression profiling in both nasal epithelium and white blood cells (WBCs); and 3) To identify expression and methylation quantitative trait loci (eQTLs and mQTLs) and perform an mQTL/eQTL-weighted study of genetic association to identify genetic variants associated with obese asthma phenotypes. APPROACH: In Aim 1, we will use cluster analysis, discriminant analysis, and recursive partitioning to define clusters of obese asthmatic children with similar phenotypic characteristics using data from a cohort of Puerto Rican children with and without asthma (Puerto Ricans share high burdens of both asthma and obesity). These clusters will be validated in two independent cohorts: CAMP (Childhood Asthma Management Program, n=1,041) and GARCS (Genetics of Asthma in Costa Rica Study, n=1,150). In Aim 2, we will obtain GW DNA methylation and gene expression profiling from nasal epithelium and WBCs in 500 children that are being recruited. We will analyze changes in nasal epithelial and WBC methylation and gene expression associated with the clusters identified in Aim 1. Genes significantly up- or down-regulated will be included in gene ontology analyses to identify pathways related to the sub-phenotypes. In Aim 3, we will identify eQTL and mQTL that are also associated with clusters from Aim 1. Then, we will look at genes and pathways from Aim 2 in mQTL/eQTL-weighted GWAS data to detect SNPs that underlie these obese asthma sub-phenotypes. FUTURE DIRECTIONS: Will include expanding sample size, multi-omic integration, functional validation, and recruitment of an independent cohort specifically designed to study obesity and asthma.